In many applications, there is a need to identify and classify audio signals. One such classification is automatically classifying an audio signal into speech, music or silence. In general, audio classification involves extracting audio features from an audio signal and classifying with a trained classifier based on the audio features.
Methods of audio classification have been proposed to automatically estimate the type of input audio signals so that manual labeling of audio signals can be avoided. This can be used for efficient categorization and browsing for large amount of multimedia data. Audio classification is also widely used to support other audio signal processing components. For example, a speech-to-noise audio classifier is of great benefits for a noise suppression system used in a voice communication system. As another example, in a wireless communications system apparatus, through audio classification, audio signal processing can implement different encoding and decoding algorithms to the signal depending on whether or not the signal is speech, music or silence.
The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section. Similarly, issues identified with respect to one or more approaches should not assume to have been recognized in any prior art on the basis of this section, unless otherwise indicated.